Reset
Showing 20 of 2,365 academic articles

Vison transformer adapter-based hyperbolic embeddings for multi-lesion segmentation in diabetic retinopathy

Zijian Wang, Haimei Lu, Haixin Yan, Hongxing Kan et al. • Scientific Reports (2023)

Abstract Diabetic Retinopathy (DR) is a major cause of blindness worldwide. Early detection and treatment are crucial to prevent vision loss, making accurate and timely diagnosis critical. Deep learning technology has shown promise in the a...

DOAJ Open Access (DOAJ) DOI: 10.1038/s41598-023-38320-5

An Efficient Distributed Reinforcement Learning Architecture for Long-Haul Communication Between Actors and Learner

Shin Morishima, Hiroki Matsutani • IEEE Access (2024)

A computing cluster that interconnects multiple compute nodes is used to accelerate distributed reinforcement learning that uses DQN (Deep Q-Network). In distributed reinforcement learning, actor nodes acquire experiences by interacting wit...

DOAJ Open Access (DOAJ) DOI: 10.1109/ACCESS.2024.3402835

Phase Extraction from Single Interferogram Including Closed-Fringe Using Deep Learning

Daichi Kando, Satoshi Tomioka, Naoki Miyamoto, Ryosuke Ueda • Applied Sciences (2019)

In an optical measurement system using an interferometer, a phase extracting technique from interferogram is the key issue. When the object is varying in time, the Fourier-transform method is commonly used since this method can extract a ph...

DOAJ Open Access (DOAJ) DOI: 10.3390/app9173529

A deep-reinforcement learning approach for optimizing homogeneous droplet routing in digital microfluidic biochips

Basudev Saha, Bidyut Das, Mukta Majumder • Nanotechnology and Precision Engineering (2023)

Over the past two decades, digital microfluidic biochips have been in much demand for safety-critical and biomedical applications and increasingly important in point-of-care analysis, drug discovery, and immunoassays, among other areas. How...

DOAJ Open Access (DOAJ) DOI: 10.1063/10.0017350

Deep learning in food category recognition

Yudong Zhang, Lijia Deng, Hengde Zhu, Wei Wang et al. • Information Fusion (2023)

Integrating artificial intelligence with food category recognition has been a field of interest for research for the past few decades. It is potentially one of the next steps in revolutionizing human interaction with food. The modern advent...

OPENALEX cc-by DOI: https://doi.org/10.1016/j.inffus.2023.101859

Deep Learning for Diabetes: A Systematic Review

Taiyu Zhu, Kezhi Li, Pau Herrero, Pantelis Georgiou • IEEE Journal of Biomedical and Health Informatics (2020)

Diabetes is a chronic metabolic disorder that affects an estimated 463 million people worldwide. Aiming to improve the treatment of people with diabetes, digital health has been widely adopted in recent years and generated a huge amount of ...

OPENALEX other-oa DOI: https://doi.org/10.1109/jbhi.2020.3040225

Deep learning applications and challenges in big data analytics

Maryam Mousaarab Najafabadi, Flavio Villanustre, Taghi M. Khoshgoftaar, Naeem Seliya et al. • Journal Of Big Data (2015)

Abstract Big Data Analytics and Deep Learning are two high-focus of data science. Big Data has become important as many organizations both public and private have been collecting massive amounts of domain-specific information, which can con...

OPENALEX cc-by DOI: https://doi.org/10.1186/s40537-014-0007-7

Relationship between perceived teacher support and learning engagement among adolescents: Mediation role of technology acceptance and learning motivation

Fuhai An, Jingyi Yu, Linjin Xi • Frontiers in Psychology (2022)

This study is aimed at investigating the relationship between perceived teacher support and learning engagement and exploring the mediation role played by technology acceptance and learning motivation. It adopted a structural equation model...

DOAJ Open Access (DOAJ) DOI: 10.3389/fpsyg.2022.992464

Jet-images — deep learning edition

Luke de Oliveira • OSTI OAI (U.S. Department of Energy Office of Scientific and Technical Information) (2022)

Building on the notion of a particle physics detector as a camera and the collimated streams of high energy particles, or jets, it measures as an image, we investigate the potential of machine learning techniques based on deep learning arch...

OPENALEX cc-by DOI: https://doi.org/10.1007/jhep07%282016%29069

Jet-images — deep learning edition

Luke de Oliveira, Michael Kagan, Lester W. Mackey, Benjamin Philip Nachman et al. • Journal of High Energy Physics (2016)

Building on the notion of a particle physics detector as a camera and the collimated streams of high energy particles, or jets, it measures as an image, we investigate the potential of machine learning techniques based on deep learning arch...

OPENALEX cc-by DOI: https://doi.org/10.1007/jhep07(2016)069

Deep learning for electroencephalogram (EEG) classification tasks: a review

Alexander Craik, Yongtian He, Jose Luis Contreras-Vidal • Journal of Neural Engineering (2019)

OBJECTIVE: Electroencephalography (EEG) analysis has been an important tool in neuroscience with applications in neuroscience, neural engineering (e.g. Brain-computer interfaces, BCI's), and even commercial applications. Many of the analyti...

OPENALEX cc-by DOI: https://doi.org/10.1088/1741-2552/ab0ab5

Distributed biconnectivity-preserving flocking with fast obstacle avoidance for UAV swarms

Jiaxin Li, Tong Duan, Peng Yi, Zhen Zhang et al. • Complex & Intelligent Systems (2026)

Abstract Obstacles in low-altitude environments force unmanned aerial vehicle (UAV) swarms to frequently alter their flight paths and communication links, which can easily cause network interruptions. It remains a significant challenge for ...

DOAJ Open Access (DOAJ) DOI: 10.1007/s40747-026-02343-y

Rider Optimization With Deep Learning Based Image Encryption for Secure Drone Communication

N. Kannaiya Raja, E. Laxmi Lydia, Thumpala Archana Acharya, K. Radhika et al. • IEEE Access (2023)

In recent years, drones or Unmanned Aerial Vehicles (UAVs) got significant attention among researchers because of their extensive application in commercial applications, border surveillance, etc. As the conventional terrestrial communicatio...

DOAJ Open Access (DOAJ) DOI: 10.1109/ACCESS.2023.3324068

A review on deep learning in medical image analysis

S. Suganyadevi, V. Seethalakshmi, K. Balasamy • International Journal of Multimedia Information Retrieval (2021)

Ongoing improvements in AI, particularly concerning deep learning techniques, are assisting to identify, classify, and quantify patterns in clinical images. Deep learning is the quickest developing field in artificial intelligence and is ef...

OPENALEX other-oa DOI: https://doi.org/10.1007/s13735-021-00218-1 PMC: 8417661